Creating, rendering and interacting with a multi-faceted audio cloud

ABSTRACT

Methods and arrangements for effecting a cloud representation of audio content. An audio cloud is created and rendered, and user interaction with at least a clip portion of the audio cloud is afforded.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.13/538,988, entitled CREATING, RENDERING AND INTERACTING WITH AMULTI-FACETED AUDIO CLOUD, filed on Jun. 29, 2012, which is incorporatedby reference in its entirety.

BACKGROUND

Conventionally, tag or word clouds are known. This helps to identifyfrequently used words in a text document. Typically, the words arearranged arbitrarily in a “weighted” representation, wherein font sizedepicts a frequency of occurrence in a document. A bigger fontcorresponds to a more frequently used word, and a smaller font to a lessfrequently used word. However, arrangements such as these are of littleuse in a variety of scenarios where a solely visual representation isnot available or otherwise difficult to access or process.

BRIEF SUMMARY

In summary, one aspect of the invention provides a method comprising:creating an audio cloud; rendering the audio cloud; and affording userinteraction with at least a clip portion of the audio cloud.

A further aspect of the invention provides a method comprising:inputting a rendered audio cloud into a user interface; and interactingwith at least a clip portion of the audio cloud.

For a better understanding of exemplary embodiments of the invention,together with other and further features and advantages thereof,reference is made to the following description, taken in conjunctionwith the accompanying drawings, and the scope of the claimed embodimentsof the invention will be pointed out in the appended claims.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 provides a representation of an audio signal.

FIG. 2 provides a visual representation of an audio cloud.

FIG. 3 provides an example of sub-word recognition applied to audiodata.

FIG. 4 sets forth a process more generally for effecting a cloudrepresentation of audio content.

FIG. 5 illustrates a computer system.

DETAILED DESCRIPTION

It will be readily understood that the components of the embodiments ofthe invention, as generally described and illustrated in the figuresherein, may be arranged and designed in a wide variety of differentconfigurations in addition to the described exemplary embodiments. Thus,the following more detailed description of the embodiments of theinvention, as represented in the figures, is not intended to limit thescope of the embodiments of the invention, as claimed, but is merelyrepresentative of exemplary embodiments of the invention.

Reference throughout this specification to “one embodiment” or “anembodiment” (or the like) means that a particular feature, structure, orcharacteristic described in connection with the embodiment is includedin at least one embodiment of the invention. Thus, appearances of thephrases “in one embodiment” or “in an embodiment” or the like in variousplaces throughout this specification are not necessarily all referringto the same embodiment.

Furthermore, the described features, structures, or characteristics maybe combined in any suitable manner in at least one embodiment. In thefollowing description, numerous specific details are provided to give athorough understanding of embodiments of the invention. One skilled inthe relevant art may well recognize, however, that embodiments of theinvention can be practiced without at least one of the specific detailsthereof, or can be practiced with other methods, components, materials,et cetera. In other instances, well-known structures, materials, oroperations are not shown or described in detail to avoid obscuringaspects of the invention.

The description now turns to the figures. The illustrated embodiments ofthe invention will be best understood by reference to the figures. Thefollowing description is intended only by way of example and simplyillustrates certain selected exemplary embodiments of the invention asclaimed herein.

It should be noted that the flowchart and block diagrams in the figuresillustrate the architecture, functionality, and operation of possibleimplementations of systems, apparatuses, methods and computer programproducts according to various embodiments of the invention. In thisregard, each block in the flowchart or block diagrams may represent amodule, segment, or portion of code, which comprises at least oneexecutable instruction for implementing the specified logicalfunction(s). It should also be noted that, in some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts, or combinations of special purpose hardware andcomputer instructions.

Specific reference will now be made herebelow to FIGS. 1-3. It should beappreciated that the processes, arrangements and products broadlyillustrated therein can be carried out on, or in accordance with,essentially any suitable computer system or set of computer systems,which may, by way of an illustrative and non-restrictive example,include a system or server such as that indicated at 12′ in FIG. 5. Inaccordance with an example embodiment, most if not all of the processsteps, components and outputs discussed with respect to FIGS. 1-3 can beperformed or utilized by way of a processing unit or units and systemmemory such as those indicated, respectively, at 16′ and 28′ in FIG. 5,whether on a server computer, a client computer, a node computer in adistributed network, or any combination thereof.

FIG. 1 provides a representation of an audio signal, and FIG. 2 providesa representation of a speech cloud. In accordance with at least oneembodiment of the invention, a multi-faceted audio cloud is generatedand rendered, wherein an audio cloud provides prominent phrases or audiosegments presented in some order of prominence. Interactivity for thecloud can also be provided.

In accordance with at least one embodiment of the invention, richpara-lingual information present in speech/audio is utilized. “Languageagnostic” methods can be employed by way of bypassing limitations inautomatic speech recognition (ASR), and a wide range of users can becatered to, from POTS (“plain old telephone service”, or landlinetelephony) to users of smart-devices. Possible applications includespoken web, call/contact centers and the music industry.

It can be recognized, in a context of at least one embodiment of theinvention, that ASR capabilities are not available for severallanguages. Further, the accuracy of ASR systems is sensitive todialects, accents, vocabulary, and other linguistic elements.Substantial resources may well be needed to build new ASR arrangements(or modifying existing ones).

As such, in accordance with at least one embodiment of the invention,speech analysis/comparison techniques can ensure wide-spreadapplicability, and language-independent sub-word units can berecognized.

In accordance with at least one embodiment of the invention, a two-stepprocess is undertaken. In a first step, audio is segmented into unitsand, in a second step, units that are “prominent” are identified. Audiosegmentation can involve voice-activity-detection (VAD) techniques,treating a contiguous chunk of speech as a unit. Alternatively, syllablesegmentation techniques can be used where each syllable or syllable-likeentity is treated as a unit. In another variant, statistical methods(e.g., sub-word ASR) can be used to estimate identity and boundaries ofsub-word units. These techniques could be used alone or in anycombination, and other techniques are certainly conceivable.

FIG. 3 provides an example of sub-word recognition applied to audiodata, in accordance with at least one embodiment of the invention. Here,an English sub-word recognition system is used on Gujarati data;pronunciation variations can also be captured in such an arrangement.(For background purposes, an illustrative example of a sub-wordrecognition system may be found in Jitendra Ajmera, Ashish Verma: “ACross-Lingual Spoken Content Search System,” INTERSPEECH 2011:2257-2260. This publication shows that an English speech recognitionsystem can be used to recognize Gujarati words such as shaakbhaji orkhatarnaak.) As shown, indicated at 301, 303 and 305 are three separateaudio documents (e.g., which each could be embodied by acustomer-operator interaction over the course of a telephone call).Here, “K-AA-P-AA-S” is recognized as a prominent sub-word. In the firstcolumn shown in each document 301/303/305, different patterns are shownthat were detected in the course of a conversation. In the secondcolumn, an integer number indicates the number of times that the patternwas detected in the document, while the third column indicates aprobability with which the pattern was found at multiple places in thedocument. Probabilities are shown here in ascending order. In somelines, above a predetermined probability threshold, “K-AA-P-AA-S” isshown in bold. The threshold can differ for different documents, but forcomparative purposes it can be preferable to keep the threshold at aconsistent level across documents. (It should further be appreciatedthat the table-like renditions shown at 301/303/305 in FIG. 3 are mainlyfor illustrative purposes, inasmuch as the values in the tables can bestored in a database table or in any other data structure. However, areport can certainly be prepared from such data in a manner that appearssimilarly to the renditions shown in FIG. 3, or in any other suitablemanner.)

In identifying units that are prominent, in accordance with at least oneembodiment of the invention, unit-comparison can be used to detect unitsthat are repeated. Employable here are frame-level speech features andDynamic Time Warping (DTW), as well as unit-level speech features andstandard distance measures. There can also be employed aggregate-levelanalysis of sub-word units estimated by statistical sub-word ASR. TF-IDF(term frequency—inverse document frequency) operations can be performedto discard non-informative units (if the corpus is available), elsethere can just be used the repetition score to identify prominence. Ahigher score points to more prominence.

With regard to a multi-faceted cloud, in accordance with at least oneembodiment of the invention, it can be noted that speech carries notjust linguistic information but is also rich in para-lingualinformation: speaker characteristics (age, gender, emotion, dialect . .. ), conversation style (multi-party vs. monologue, casual vs. formal .. . ). The same linguistic message from a friend vs. from a strangercould convey a different meaning/value. The significance of prominencecan vary based on the time of prominence of an audio-unit. It can thusbe appreciated that every audio unit is likely to have facets such asthese and others as meta-data.

Cloud rendering, in accordance with at least one embodiment of theinvention, can be carried out in a variety of ways. Generally, differentaspects of audio rendering can be used to convey various facets of theaudio cloud, such as: a volume of rendered units corresponding tooccurrence frequency in the audio clip; a representative unit renderedcorresponding to a speaker who spoke that unit most often in the clip; aperceived distance/location of the unit corresponding to asocial-network closeness of the listener and the unit-speaker; aperceived direction of the rendered unit corresponding to a time ofoccurrence of the unit in the clip (e.g., audio played from the leftchannel corresponding to a clip occurring at the beginning of the audioand right channel corresponding to a clip occurring at the end of theaudio). Other such aspects of rendering can be utilized to conveyvarious facets of the cloud, while units can be rendered sequentially orwith temporal overlap

Visual rendering is provided in accordance with at least one embodimentof the invention. Here, audio-units (visually displayed as audiosignals) can be arranged in the order of decreasing frequency ofoccurrence. A display size can correspond to a frequency of occurrence,with a particular arrangement reflecting a time of occurrence in theclip. Hovering/clicking on a unit can play a corresponding audio unitand also highlight its occurrence in the original audio. The visualrendering can also be arranged like a text tag cloud where instead oftext, there are audio signals.

Cloud interaction, in accordance with at least one embodiment of theinvention, can involve dynamically re-generating or modifying therendering of the cloud based on user-inputs. A user can use gestures toindicate: part of the clip to be “clouded” (where “clouded” refers togenerating an audio cloud for that part of the clip); audio fromspeaker(s) to be “clouded”; an audio unit to be recalled from the clip;sample gestures (e.g., left-right movement, nod, shake, frequency oftaps). Visually, the cloud can be also be generated only for the audioportion displayed/selected on the screen.

FIG. 4 sets forth a process more generally for effecting a cloudrepresentation of audio content, in accordance with at least oneembodiment of the invention. It should be appreciated that a processsuch as that broadly illustrated in FIG. 4 can be carried out onessentially any suitable computer system or set of computer systems,which may, by way of an illustrative and non-restrictive example,include a system such as that indicated at 12′ in FIG. 5. In accordancewith an example embodiment, most if not all of the process stepsdiscussed with respect to FIG. 4 can be performed by way a processingunit or units and system memory such as those indicated, respectively,at 16′ and 28′ in FIG. 5.

As shown in FIG. 4, in accordance with at least one embodiment of theinvention, an audio cloud is created (402) and rendered (404), and userinteraction with at least a clip portion of the audio cloud is afforded(406).

Referring now to FIG. 5, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10′ is only one example of asuitable cloud computing node and is not intended to suggest anylimitation as to the scope of use or functionality of embodiments of theinvention described herein. Regardless, cloud computing node 10′ iscapable of being implemented and/or performing any of the functionalityset forth hereinabove. In accordance with embodiments of the invention,computing node 10′ may not necessarily even be part of a cloud networkbut instead could be part of another type of distributed or othernetwork, or could represent a stand-alone node. For the purposes ofdiscussion and illustration, however, node 10′ is variously referred toherein as a “cloud computing node”.

In cloud computing node 10′ there is a computer system/server 12′, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12′ include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12′ may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12′ may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 5, computer system/server 12′ in cloud computing node10 is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12′ may include, but are notlimited to, at least one processor or processing unit 16′, a systemmemory 28′, and a bus 18′ that couples various system componentsincluding system memory 28′ to processor 16′.

Bus 18′ represents at least one of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnects (PCI) bus.

Computer system/server 12′ typically includes a variety of computersystem readable media. Such media may be any available media that areaccessible by computer system/server 12′, and includes both volatile andnon-volatile media, removable and non-removable media.

System memory 28′ can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30′ and/or cachememory 32′. Computer system/server 12′ may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34′ can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18′ by at least one datamedia interface. As will be further depicted and described below, memory28′ may include at least one program product having a set (e.g., atleast one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 40′, having a set (at least one) of program modules 42′,may be stored in memory 28′ (by way of example, and not limitation), aswell as an operating system, at least one application program, otherprogram modules, and program data. Each of the operating systems, atleast one application program, other program modules, and program dataor some combination thereof, may include an implementation of anetworking environment. Program modules 42′ generally carry out thefunctions and/or methodologies of embodiments of the invention asdescribed herein.

Computer system/server 12′ may also communicate with at least oneexternal device 14′ such as a keyboard, a pointing device, a display24′, etc.; at least one device that enables a user to interact withcomputer system/server 12; and/or any devices (e.g., network card,modem, etc.) that enable computer system/server 12′ to communicate withat least one other computing device. Such communication can occur viaI/O interfaces 22′. Still yet, computer system/server 12′ cancommunicate with at least one network such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 20′. As depicted, network adapter 20′communicates with the other components of computer system/server 12′ viabus 18′. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 12′. Examples include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

It should be noted that aspects of the invention may be embodied as asystem, method or computer program product. Accordingly, aspects of theinvention may take the form of an entirely hardware embodiment, anentirely software embodiment (including firmware, resident software,micro-code, etc.) or an embodiment combining software and hardwareaspects that may all generally be referred to herein as a “circuit,”“module” or “system.” Furthermore, aspects of the invention may take theform of a computer program product embodied in at least one computerreadable medium having computer readable program code embodied thereon.

Any combination of one or more computer readable media may be utilized.The computer readable medium may be a computer readable signal medium ora computer readable storage medium. A computer readable storage mediummay be, for example, but not limited to, an electronic, magnetic,optical, electromagnetic, infrared, or semiconductor system, apparatus,or device, or any suitable combination of the foregoing. More specificexamples (a non-exhaustive list) of the computer readable storage mediumwould include the following: an electrical connection having at leastone wire, a portable computer diskette, a hard disk, a random accessmemory (RAM), a read-only memory (ROM), an erasable programmableread-only memory (EPROM or Flash memory), an optical fiber, a portablecompact disc read-only memory (CD-ROM), an optical storage device, amagnetic storage device, or any suitable combination of the foregoing.In the context of this document, a computer readable storage medium maybe any tangible medium that can contain, or store, a program for use by,or in connection with, an instruction execution system, apparatus, ordevice.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wire line, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of theinvention may be written in any combination of at least one programminglanguage, including an object oriented programming language such asJava®, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer (device), partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer, or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider).

Aspects of the invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products. It will be understood that eachblock of the flowchart illustrations and/or block diagrams, andcombinations of blocks in the flowchart illustrations and/or blockdiagrams, can be implemented by computer program instructions. Thesecomputer program instructions may be provided to a processor of ageneral purpose computer, special purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions, which execute via the processor of the computer orother programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture. Such an article of manufacturecan include instructions which implement the function/act specified inthe flowchart and/or block diagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

This disclosure has been presented for purposes of illustration anddescription but is not intended to be exhaustive or limiting. Manymodifications and variations will be apparent to those of ordinary skillin the art. The embodiments were chosen and described in order toexplain principles and practical application, and to enable others ofordinary skill in the art to understand the disclosure.

Although illustrative embodiments of the invention have been describedherein with reference to the accompanying drawings, it is to beunderstood that the embodiments of the invention are not limited tothose precise embodiments, and that various other changes andmodifications may be affected therein by one skilled in the art withoutdeparting from the scope or spirit of the disclosure.

What is claimed is:
 1. A method comprising: segmenting audio provided ina first language not having available automatic speech recognitioncapabilities into speech units, wherein said segmenting comprisesemploying a language sub-word recognition technique selected from thegroup consisting of: a statistical system for sub-word unit recognition;a voice-activity-detection technique; and a syllable segmentationtechnique, wherein the language sub-word recognition technique comprisesutilizing a sub-word recognition technique of a second language havingavailable automatic speech recognition capabilities and different fromthe first language of the audio; identifying prominent speech units,wherein identifying comprises detecting a repeated speech unit byidentifying speech patterns within the audio and using a languageagnostic speech unit comparison technique, wherein the language agnosticspeech unit comparison technique comprises a technique where a languageassociated with the speech unit is disregarded; wherein the identifyingfurther comprises determining a frequency of occurrence of a speech unitand wherein a prominent speech unit comprises a speech unit that exceedsa predetermined frequency of occurrence threshold; creating an audiocloud comprising audio signals of the prominent speech units, whereineach of the audio signals comprise a playable audio unit that whenplayed provides an audible output of the corresponding prominent speechunit; rendering the audio cloud, wherein the audio cloud comprises avisual representation of the audio signals, wherein the audio signalsare arranged in order of decreasing frequency of occurrence and whereina volume of the audio signals is based upon the frequency of occurrence;and affording user interaction with at least a clip portion of the audiocloud.
 2. The method according to claim 1, comprising determiningprominence of speech units.
 3. The method according to claim 2, whereinsaid determining comprises determining at least one member selected fromthe group consisting of: frequency of speech units; spread of occurrenceof speech units; distribution of speech units across at least one clip;and TF-IDF.
 4. The method according to claim 1, wherein said segmentingcomprises encoding audio para-lingual information in the units.
 5. Themethod according to claim 1, wherein said rendering comprises at leastone member selected from the group consisting of: audio-based rendering;and visual-display-based rendering.
 6. The method according to claim 5,wherein said audio-based rendering comprises employing aspects ofplayback to convey aspects of the audio cloud.
 7. The method accordingto claim 6, wherein the aspects of the audio cloud comprise at least onemember selected from the group consisting of: a volume of rendered unitscorresponding to occurrence frequency in the clip portion; arepresentative unit rendered corresponding to a speaker who spoke thatunit most often in the clip portion; a perceived location of the unitcorresponding to a social-network closeness of a listener and a speaker;and a perceived direction of a rendered speech unit corresponding to atime of occurrence of the unit in the clip portion.
 8. The methodaccording to claim 5, wherein said visual-display-based renderingcomprises employing aspects of visual order to convey aspects of theaudio cloud.
 9. The method according to claim 8, wherein the aspects ofvisual order comprise at least one member selected from the groupconsisting of: audio units visually displayed as audio signals; audiounits visually arranged in an order of decreasing frequency ofoccurrence; a display size of an audio unit corresponding to a frequencyof occurrence; a visual arrangement reflecting a time of occurrence ofan audio unit in the clip portion; a highlighting of occurrence of anaudio unit in the clip portion in response to clicking on a visualrepresentation of an audio unit; and a tag cloud comprising a visualrendition of audio signals.
 10. The method according to claim 1, whereinsaid creating and rendering steps are interactive based on user input.11. The method according to claim 10, wherein said creating andrendering steps are modifiable in response to user input.
 12. The methodaccording to claim 11, wherein the user input includes at least onemember selected from the group consisting of: a user gesture to indicatea part of the clip portion to be clouded; a user gesture to indicate anaudio portion from a speaker to be clouded; and a user gesture forrecalling an audio unit from the clip.
 13. A method comprising:inputting a rendered audio cloud at a user interface, wherein the audiocloud comprises a visual representation of audio signals represented asclip portions, wherein each of the audio signals comprise a playableaudio unit that when played provides an audible output of thecorresponding prominent speech unit, wherein the audio signals arearranged in order of decreasing frequency of occurrence, and wherein avolume of the audio signals is based upon the frequency of occurrenceand the rendered audio cloud including: speech units of a first languagenot having available automatic speech recognition capabilities detectedvia at least one a language sub-word recognition technique selected fromthe group consisting of: a statistical system for sub-word unitrecognition, and a speech-analysis technique, wherein the languagesub-word recognition technique comprises utilizing a sub-wordrecognition technique of a second language having available automaticspeech recognition capabilities and different from the first language ofthe audio; and an identification of prominent speech units via detectinga repeated speech unit by identifying speech patterns within the audioand using a language agnostic speech unit comparison technique andwherein the identification comprises determining a frequency ofoccurrence of a speech unit and wherein a prominent speech unitcomprises a speech unit that exceeds a predetermined frequency ofoccurrence threshold; and interacting with at least one of the clipportions of the audio cloud.
 14. A method comprising: segmenting audioprovided in a first language not having available automatic speechrecognition capabilities into speech units; wherein segmenting comprisesemploying a language sub-word recognition technique selected from thegroup consisting of: a statistical system for sub-word unit recognition;a voice-activity-detection technique; and a syllable segmentationtechnique, wherein the language sub-word recognition technique comprisesutilizing a sub-word recognition technique of a second language havingavailable automatic speech recognition capabilities and different fromthe first language of the audio; identifying, by employing alanguage-agnostic speech unit comparison technique, prominent speechunits within the audio, wherein the language agnostic techniquecomprises a method where a language associated with the speech unit isdisregarded, wherein the identifying comprises detecting a repeatedspeech unit by identifying speech patterns within the audio; wherein theidentifying further comprises determining a frequency of occurrence of aspeech unit and wherein a prominent speech unit comprises a speech unitthat exceeds a predetermined frequency of occurrence threshold; creatingan audio cloud comprising audio signals of the identified prominentspeech units, wherein each of the audio signals comprise a playableaudio unit that when played provides an audible output of thecorresponding prominent speech unit; rendering the audio cloudcomprising a visual representation of the audio signals of theidentified prominent units, wherein the audio signals are arranged inorder of decreasing frequency of occurrence and wherein a volume of theaudio signals is based upon the frequency of occurrence.
 15. The methodaccording to claim 14, wherein a language sub-word recognition techniquecomprises a speech analysis technique where accuracy of the technique isnot dependant on a language and language characteristics of a speaker.16. The method according to claim 14, wherein the audio signals withinthe rendered audio cloud are presented in an order based upon aprominence of the unit.
 17. The method according to claim 14, wherein toidentify prominent units comprises employing term frequency—inversedocument frequency operations.
 18. The method according to claim 14,comprising computer readable program code configured to detect speechunits.
 19. The method according to claim 14, wherein to render the audiocloud comprises a type of rendering selected from the group consistingof: audio-based rendering; and visual-display-based rendering.